Definition of Multicollinearity. Meaning of Multicollinearity. Synonyms of Multicollinearity

- statistics, multicollinearity or collinearity is a situation where the predictors in a regression model are linearly dependent. Perfect multicollinearity refers...
- used to calculate it. This is the problem of multicollinearity in moderated regression. Multicollinearity tends to cause coefficients to be estimated with...
- reason for the use of sensitivity analysis is to detect multicollinearity. Multicollinearity is the phenomenon where the correlation between two variables...
- vector-of-ones variable were also present, this would result in perfect multicollinearity, so that the matrix inversion in the estimation algorithm would be...
- even more important. One major use of PCR lies in overcoming the multicollinearity problem which arises when two or more of the explanatory variables...
- other X variables) on the right hand side. Analyze the magnitude of multicollinearity by considering the size of the VIF⁡(α^i){\displaystyle \operatorname...
- In practice, we rarely face perfect multicollinearity in a data set. More commonly, the issue of multicollinearity arises when there is a "strong linear...
- predictors has more variables than observations, and when there is multicollinearity among X values. By contrast, standard regression will fail in these...
- regression is a general way of handling this issue. Lack of perfect multicollinearity in the predictors. For standard least squares estimation methods,...
- Analysis of covariance (ANCOVA) is a general linear model that blends ANOVA and regression. ANCOVA evaluates whether the means of a dependent variable...